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Observe: as outlined while in the docs, flatten requires a list of lists. See beneath on flattening additional irregular inputs.
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The fact that list slices create a duplicate is a function of lists by themselves. If you're slicing Innovative objects just like a Pandas DataFrame, it may return a watch on the initial, instead of a duplicate.
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involve the factor at this index, defaults to size from the sequence currently being sliced, that's, as many as and such as the finish.
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Remember the fact that the result of slicing a collection is an entire new collection. Also, when using slice notation in assignments, the duration from the slice assignments do not must be the identical.
It exploits the fact that if i evaluates to False for 0 and also to True for all other values produced via the operate array(). Therefore the list comprehension evaluates as follows:
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After making use of it a tad I realise that The best description is that it is exactly the same because the arguments in a for loop...
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